Embodiments of the present specification generally relate to a wind turbine and more specifically to systems and methods for controlling a wind turbine.
Wind turbines are growing in popularity as a means of generating energy due to the renewable nature of the energy so generated and lack of pollution. The wind turbines generally have a rotor with a plurality of blades coupled to a generator. The power extraction capability and secure operation of a wind turbine typically depends on various factors including wind speed. For example, knowledge of potential wind speeds that will impact the rotor of the wind turbine in the following few seconds may be helpful in controlling the wind turbine for optimal power extraction.
Wind speeds are typically measured by an anemometer such as a cup anemometer. However, anemometers are incapable of predicting the potential wind speeds that will impact the rotor of the wind turbine in the imminent future. Laser radar systems (LIDARs) have been employed for measuring wind speeds and direction of wind for many years. These LIDARs have been used to measure wind shear, turbulence and wake vortices in both military and civil applications. Typically, the laser radar system (LIDAR) operates by scattering radiation from natural aerosols (for example, dust, pollen, water droplets, and the like) and measuring the Doppler shift between outgoing and returning radiation. In order to measure wind speed and direction it is usual to scan the LIDAR, typically using a conical scan or multiple fixed beams to allow a wind vector to be intersected at a range of angles, thereby enabling a true (3D) velocity vector to be deduced. Other scanning patterns may also be used to determine the true velocity vector. However, the accuracy of determining the true velocity vector is dependent on knowledge regarding the direction of the LIDAR.
One of the advantages of LIDAR includes prediction of the potential wind speeds approaching the rotor of the wind turbine. For example, LIDARs may be used for providing wind speed measurements upto 400 m in front or ahead of the rotor of the wind turbine. Accordingly, the LIDAR may provide information regarding approaching wind speeds to a wind turbine controller in advance, thereby increasing the controller's available reaction time and allowing pitch actuation to occur in advance to mitigate wind disturbance effects. The wind turbine controller may use feed-forward control algorithms to improve load mitigation and controller performance.
Currently available LIDARs for use with wind turbines are impacted by surrounding atmospheric conditions and many other factors such as blade positions. Consequently, potential wind speeds measured by the LIDARs may be erroneous. Many such LIDARs provide a Boolean indicator (0 and 1) that indicates validity of signals representative of potential wind speeds. The Boolean indicators are often based on a signal to noise ratio (SNR) or measurement quality indication. The potential wind speeds that correspond to a zero Boolean indicator may be discarded due to lack of confidence. Usage of the Boolean indicator may impact availability of potential wind speeds. For example, usage of the Boolean indicator may result in substantially low or zero availability of potential wind speeds for a period of time. Non-availability or lower availability of potential wind speeds may impact the efficiency of wind turbines that use wind speeds determined by LIDARs.
Atmospheric conditions such as wind speed, turbulence intensity and turbulence length scales may influence wind speeds of wind travelling from LIDAR measurement points to the wind turbine. As per Taylor's hypothesis, in a high wind coherency situation, wind field variations travel from the LIDAR measurement points to the wind turbine almost unchanged. Hence, wind speeds determined during high wind coherency situations using LIDARs are typically accurate. However, in a low wind coherency situation, wind field variations may entirely change while travelling from the LIDAR measurement points to the wind turbine. Accordingly, wind coherency plays an important role in determination of wind speeds.